VGT: Prefix Handling for Checkpoint State Dictionary

When attempting to load model weights from a checkpoint in VGT, the model's state dictionary keys do not match the checkpoint keys due to potential prefixing issues. This mismatch results in parameters not being loaded correctly, which lead to a significant increase in "total_loss".

In my opinion, no prefixes are necessary. However, if prefixes are needed, we can implement a simple check to address this issue.

In MyDetectionCheckpointer.py, check if prefixes are required for the keys:
```python
if needs_prefix(checkpoint_state_dict, model_state_dict):
new_checkpoint_state_dict = {}
for k in checkpoint_state_dict.keys():
new_checkpoint_state_dict[append_prefix(k)] = checkpoint_state_dict[k]

for k in DiT_checkpoint_state_dict.keys():
new_checkpoint_state_dict[DiT_append_prefix(k)] = DiT_checkpoint_state_dict[k]

checkpoint_state_dict = new_checkpoint_state_dict
```

Here’s the function to determine if prefixes are needed:
```python
def needs_prefix(checkpoint_state_dict, model_state_dict):
for k in checkpoint_state_dict.keys():
if k not in model_state_dict:
prefixed_key = append_prefix(k)
if prefixed_key in model_state_dict:
return True
return False
```

After implementing these changes, re-training from a checkpoint works flawlessly.